Statistical analyses. Preliminary analyses. All data will be inspected employing quality control procedures. Descriptive statistics will be computed for every study variable to ensure that all data values are within expected ranges and to eliminate any data errors that may have occurred. If needed, in the event that some of our variables are not normally distributed, we will transform these variables using log transformations or use non-parametric statistics. A mixed model analysis program (using SAS Proc Mixed) for growth models will be used to assess our 4 primary hypotheses. Missing data will be handled using the full information likelihood algorithm, which uses all the data available for all participants. To assess our secondary hypotheses, structural equation models will be used. The secondary analyses will be conducted across several domains, modeled as latent variables.